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Record W2058840776 · doi:10.1177/0008417414567529

Empowering people to change occupational behaviours to address critical global issues

2015· article· en· W2058840776 on OpenAlexvenueno aff
Moses N. Ikiugu, Madeline A. Westerfield, Jamie M. Lien, Emily R. Theisen, Shana Cerny, Ranelle Nissen

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentOccupational therapyPsychological interventionPsychologyIntervention (counseling)Applied psychologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The greatest threat to human well-being in this century is climate change and related global issues. PURPOSE: We examined the effectiveness of the Modified Instrumentalism in Occupational Therapy model as a framework for facilitating occupational behaviour change to address climate change and related issues. METHOD: Eleven individuals participated in this mixed-methods single-subject-design study. Data were gathered using the Modified Assessment and Intervention Instrument for Instrumentalism in Occupational Therapy and Daily Occupational Inventories. Quantitative data were analyzed using two- and three-standard deviation band methods. Qualitative data were analyzed using heuristic phenomenological procedures. FINDINGS: Occupational performance changed for five participants. Participants' feelings shifted from frustration and helplessness to empowerment and a desire for action. They felt empowered to find occupation-based solutions to the global issues. IMPLICATIONS: Occupation-based interventions that increase personal awareness of the connection between occupational performance and global issues could empower people to be agents for action to ameliorate the issues.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.513
GPT teacher head0.604
Teacher spread0.091 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2015
Admission routes1
Has abstractyes

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